Deep Learning to Estimate Model Biases in an Operational NWP Assimilation System by Patrick Laloyaux, Thorsten Kurth, Peter Dominik Dueben, David Hall

“…Abstract Model bias is one of the main obstacles to improved accuracy and reliability in numerical weather prediction conducted with state‐of‐the‐art atmospheric models. …”
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Novel integrated computational AMP discovery approaches highlight diversity in the helminth AMP repertoire. by Allister Irvine, Darrin McKenzie, Ciaran J McCoy, Robert L J Graham, Ciaren Graham, Sharon A Huws, Louise E Atkinson, Angela Mousley

“…This study highlights limitations in the homology-based approaches, used to identify putative nematode AMPs, for the characterisation of flatworm AMPs, and reveals that innovative algorithmic AMP prediction approaches provide an alternative strategy for novel helminth AMP discovery. …”
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Numerical Simulation of Basic Properties of Full-Steel Slag Aggregate Concrete by Zhu Bian, Yuan Fang, Feng Yu, Xuliang Wang, Guosheng Xiang

“…In this study, the bit-level table of orthogonal test is adopted as the coding form of Genetic Algorithm (GA), and a Back Propagation (BP) neural network prediction model of the basic properties of full steel slag aggregate concrete (FSSAC) is established, and the experiment data are validated with good agreement. …”
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Exploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis: a bibliometric analysis (2004–2023) by Jian-cheng Lou, Xiao-fen Yu, Jian-jun Ying, Da-qiao Song, Wen-hua Xiong

“…The development in this field is marked by a coexisting pattern of interdisciplinary integration and refinement within major disciplinary branches.ConclusionThe application of machine learning in the early prediction and personalized medical plans for stroke patients using neuroimaging characteristics offers significant value. …”
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Electricity pinch analysis method for flexibility supply-demand matching in power systems by Yaling Mao, Tiejiang Yuan, Xueqin Tian, Yue Teng

“…By relying directly on frequency-domain characteristic parameters for resource planning, the proposed approach markedly reduces dependence on high-precision sequential forecasts and significantly mitigates the impact of power-prediction uncertainty on planning results.…”
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Optimizing solar PV systems using fuzzy logic for Climate-Resilient Healthcare infrastructure in Kyrgyzstan by Nivine Guler, Zied Ben Hazem, Ali Gunes

“…Also, the proposed scheme showed 3% prediction error when checked with the PVWatts calculator. …”
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Optimizing sustainable blended concrete mixes using deep learning and multi-objective optimization by Rupesh Kumar Tipu, Preeti Rathi, Kartik S. Pandya, Vijay R. Panchal

“…A DNN model receives training through a wide dataset which includes multiple mix parameters along with curing conditions for accurate compressive strength prediction. The Bayesian hyperparameter tuning technique produces an optimal network configuration which delivers an average $$R^2$$ of 0.936 together with an RMSE of 5.71 MPa during 5-fold cross-validation. …”
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Cross-Domain Fake Review Detection via Orthogonal Counterfactual Representations by Richa Gupta, Vinita Jindal, Indu Kashyap

“…Working of the proposed COAT is divided in three phases: 1) two-step masking to remove source-specific cues, 2) counterfactual generation using BERT, followed by orthogonal alignment via Procrustes algorithm, and 3) training and prediction using a Bi-LSTM classifier in a zero-shot setting. …”
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A Statistical Optimization Method for Sound Speed Profiles Inversion in the South China Sea Based on Acoustic Stability Pre-Clustering by Zixuan Zhang, Ke Qu, Zhanglong Li

“…Disturbance mode principal component analysis is first used to extract characteristic parameters, and then a machine learning clustering algorithm is adopted to pre-classify SSP samples according to acoustic stability. …”
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Equatorial convection controls boreal summer intraseasonal oscillations in the present and future climates by Aditya Kottapalli, P. N. Vinayachandran

“…The study implies that with a correct representation of BSISO’s equatorial convection, the prediction of BSISO and extreme rainfall associated with BSISOs becomes more reliable.…”
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Enhancing multiclass brain tumor diagnosis using SVM and innovative feature extraction techniques by Mustafa Basthikodi, M. Chaithrashree, B. M. Ahamed Shafeeq, Ananth Prabhu Gurpur

“…This approach will not only improves categorization performance but also improves efficacy of computation, making it a robust and effective method for multiclass brain tumor prediction.…”
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Machine Learning-Based Environment-Aware GNSS Integrity Monitoring for Urban Air Mobility by Oguz Kagan Isik, Ivan Petrunin, Antonios Tsourdos

“…The proposed Natural Gradient Boosting Protection Level (NGB-PL) method, leveraging the uncertainty prediction capabilities of the NGB algorithm, demonstrated superior performance in estimating protection levels compared to the classical methods. …”
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A Comparative Study of Three-Dimensional Flow Based, Geometric, and Empirical Tortuosity Models in Carbonate and Sandstone Reservoirs by Benedicta Loveni Melkisedek, Yoevita Emeliana, Irwan Ary Dharmawan

“…This comprehensive comparison underscores the importance of incorporating multiple pore-scale parameters for robust tortuosity prediction, improving the understanding of flow behavior in heterogeneous reservoir rocks.…”
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A Method for Developing a Digital Terrain Model of the Coastal Zone Based on Topobathymetric Data from Remote Sensors by Mariusz Specht, Marta Wiśniewska

“…They were processed using the “Depth Prediction” plug-in based on the Support Vector Regression (SVR) algorithm, which was implemented in the QGIS software as part of the INNOBAT project. …”
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Conditional distributionally robust dispatch for integrated transmission-distribution systems via distributed optimization by Jie Li, Xiuli Wang, Zhicheng Wang, Zhenzi Song

“…Also, the distributed algorithm reduces solution time and scales well under various ITDSs.…”
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Early Warning for the Construction Safety Risk of Bridge Projects Using a RS-SSA-LSSVM Model by Gang Li, Ruijiang Ran, Jun Fang, Hao Peng, Shengmin Wang

“…The proposed model integrates a rough set (RS), the sparrow search algorithm (SSA), and the least squares support vector machine (LSSVM). …”
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Landslide Segmentation in High-Resolution Remote Sensing Images: The Van–UPerAttnSeg Framework with Multi-Scale Feature Enhancement by Chang Li, Quan Zou, Guoqing Li, Wenyang Yu

“…In addition, this study introduces a sliding window algorithm based on Gaussian fusion as a post-processing method, which optimizes the prediction of landslide edge in high-resolution remote sensing images and ensures the context reasoning ability of the model. …”
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Investigation of the application of an automated monitoring system for detecting transmission cable deterioration in Nigeria: A case study of transmission cable lines between Offa... by C.S. Omoniabipi, R. Agbadede, K.C. Emmanuel, O.J. Adewuni, I. Allison

“…The study successfully demonstrated the prediction of overload conditions using neural networks, with minimal errors illustrated through confusion matrices and performance plots.…”
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Prognostic and therapeutic relevance of IL2RG-related LncRNAs in clear cell renal cell carcinoma by Weijing Hu, Bo Wu, Yongquan Chen, Xiaoling Guo, Xiaosong Wang, Dongwen Wang

“…The 6-IRLs model provides a robust tool for predicting prognosis and guiding therapeutic decisions.…”
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Round, just-below, or precise prices? Cultural differences in the prevalence of price endings in E-commerce by Alfio Ventura, Alfio Ventura, Alfio Ventura, Eve Sarah Troll, Meikel Soliman, David D. Loschelder

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